One of factors for letting an automobile safely travel includes pressure of a tire. When the pressure is decreased to less than a proper value, operating stability and fuel consumption are deteriorated, so that a tire burst may sometimes be caused. Therefore, a tire pressure monitoring system (TPMS) for detecting a decrease in tire pressure and issuing an alarm so as to urge a driver to take a proper action is an important technique from a view of protecting an environment and ensuring safety of the driver.
The conventional monitoring system can be classified into two types including a direct detection type and an indirect detection type. The direct detection type is to directly measure the pressure of the tire by incorporating pressure sensors inside a tire wheel. Although the decrease in the pressure can be detected with high precision, some disadvantages in terms of technique and cost remain, the disadvantages including problems in battery life, maintenance, and fault tolerance in an actual environment.
Meanwhile, the indirect detection type is a method for estimating the pressure from rotation information of the tire, and can be finely classified into a Dynamic Loaded Radius (DLR) method and a Resonance Frequency Mechanism (RFM) method. Among them, the RFM method can solve problems in the DLR method (problems such as incapability of detecting four-wheel simultaneous under-inflation due to the basic principle that rotation speed is relatively compared among wheels), and various techniques are proposed.
The RFM method utilizes a characteristic that a torsional resonance frequency of the tire is lowered by the under-inflation and time-series estimates the torsional resonance frequency of the tire from rotation speed information or rotation acceleration information of the tire so as to detect the decrease in the pressure of the tire.
However, at the time of estimating the resonance frequency of the tire in the RFM method, when there is a peak caused by a noise in the vicinity of a tire resonance frequency in a wheel speed spectrum, estimate precision of the resonance frequency is lowered. For example, when a periodic noise represented by an engine noise is superimposed on the vicinity of the resonance frequency of the tire, the estimate precision of the resonance frequency is largely influenced.
A major cause of the engine noise is rotation unevenness and torque unevenness of the engine. Thus, in general, the engine noise appears in left and right wheels of driving wheels in the same phase. In order to eliminate such an influence of the noise of the same phase, obtainment of a difference in wheel speed between the left and right wheels is proposed (for example, refer to Patent Literature 1 and Non-Patent Literature 1). In tire pressure estimate methods described in Patent Literature 1 and Non-Patent Literature 1, in consideration with the fact that the above engine noise appears in left and right wheels in the same phase, a difference in wheel speed between the left and right wheels is obtained for removing the engine noise.
Cancellation of a noise by subjecting wheel speed signals to FFT processing, smoothing a spectrum by averaging processing or the like, and cutting off a peak caused by the noise is proposed (for example, refer to Patent Literature 2).